A breathing-synchronized neuromuscular electrical stimulation algorithm for addressing respiratory impairments after cervical spinal cord injury

Cervical spinal cord injuries (cSCI) induce profound denervation in respiratory muscles leading to hypoventilation that compromises quality of life. Respiratory neuromuscular electrical stimulation of extra-diaphragmatic muscles (rNMES) could be a non-invasive approach to improve respiratory function following cSCI. However, it is critical to first synchronize rNMES with spontaneous breathing. An Ordinary Differential Equation (ODE) was solved and fitted to experimental breathing signals obtained via plethysmography in ten mice. Optimal stimulation ODE-based parameters were identified for intercostal and abdominal muscle stimulation for breathing-synchronized rNMES training. Feasibility was tested on tolerance to repetitive anesthesia and stimulation for ten training sessions in six mice. The ODE-based breathing signals matched the experimental ones with an average coefficient of determination (R{superscript 2}) of 81%. The developed algorithm, Algostim, provided average theoretical optimal times of 0.12 s for intercostal and 0.32 s for abdominal muscles contraction. Feasibility and tolerance to rNMES were favorable after ten sessions. This innovative mathematical approach to rNMES allows optimal stimulation of respiratory muscles while accounting for spontaneous breathing rate. Algostim established a framework for personalized rNMES therapies, enabling the delivery of standardized stimulation parameters and allowing detailed investigation into the underlying mechanisms of rNMES.